Universal Learning Networks with Branch Control

Kotaro Hirasawa, Jinglu Hu, Qingyu Xiong, Junichi Murata, Yuhki Shiraishi

研究成果: Contribution to conferencePaper査読

1 被引用数 (Scopus)

抄録

In this paper, Universal Learning Networks with Branch Control (BrcULNs) are proposed, which consist of basic networks and branch control networks. The branch control network can be used to determine which branches of the basic network should be connected or disconnected. This determination depends on the inputs or the network flows of the basic network. Therefore, by using the BrcULNs, locally functions distributed networks can be realized depending on the values of the inputs of the network or the information of the network flows. The proposed network is applied to some function approximation problems. The simulation results show that the BrcULNs exhibit better performance than the conventional networks with comparable complexity.

本文言語英語
ページ97-102
ページ数6
出版ステータス出版済み - 1 1 2000
イベントInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
継続期間: 7 24 20007 27 2000

その他

その他International Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy
Period7/24/007/27/00

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

引用スタイル